Dataset statistics
| Dataset A | Dataset B | |
|---|---|---|
| Number of variables | 12 | 12 |
| Number of observations | 446 | 446 |
| Missing cells | 448 | 434 |
| Missing cells (%) | 8.4% | 8.1% |
| Duplicate rows | 0 | 0 |
| Duplicate rows (%) | 0.0% | 0.0% |
| Total size in memory | 45.3 KiB | 45.3 KiB |
| Average record size in memory | 104.0 B | 104.0 B |
Variable types
| Dataset A | Dataset B | |
|---|---|---|
| Numeric | 5 | 5 |
| Categorical | 4 | 4 |
| Text | 3 | 3 |
| Dataset A | Dataset B | |
|---|---|---|
Age has 86 (19.3%) missing values | Age has 87 (19.5%) missing values | Missing |
Cabin has 362 (81.2%) missing values | Cabin has 345 (77.4%) missing values | Missing |
PassengerId has unique values | PassengerId has unique values | Unique |
Name has unique values | Name has unique values | Unique |
SibSp has 297 (66.6%) zeros | SibSp has 312 (70.0%) zeros | Zeros |
Parch has 339 (76.0%) zeros | Parch has 344 (77.1%) zeros | Zeros |
| Alert not present in this dataset | Survived is highly overall correlated with Sex | High Correlation |
| Alert not present in this dataset | Sex is highly overall correlated with Survived | High Correlation |
| Alert not present in this dataset | Fare has 5 (1.1%) zeros | Zeros |
Reproduction
| Dataset A | Dataset B | |
|---|---|---|
| Analysis started | 2023-10-10 11:13:35.413766 | 2023-10-10 11:13:43.170087 |
| Analysis finished | 2023-10-10 11:13:43.167627 | 2023-10-10 11:13:49.849362 |
| Duration | 7.75 seconds | 6.68 seconds |
| Software version | ydata-profiling v0.0.dev0 | ydata-profiling v0.0.dev0 |
| Download configuration | config.json | config.json |
PassengerId
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 446 | 446 |
| Distinct (%) | 100.0% | 100.0% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 457.25112 | 451.40135 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 2 | 2 |
| Maximum | 891 | 891 |
| Zeros | 0 | 0 |
| Zeros (%) | 0.0% | 0.0% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 2 | 2 |
| 5-th percentile | 51 | 61.25 |
| Q1 | 224.25 | 241.5 |
| median | 467 | 451 |
| Q3 | 679.75 | 664.75 |
| 95-th percentile | 846.75 | 843.5 |
| Maximum | 891 | 891 |
| Range | 889 | 889 |
| Interquartile range (IQR) | 455.5 | 423.25 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 256.16883 | 252.32049 |
| Coefficient of variation (CV) | 0.56023663 | 0.55897151 |
| Kurtosis | -1.2043126 | -1.185294 |
| Mean | 457.25112 | 451.40135 |
| Median Absolute Deviation (MAD) | 223 | 212.5 |
| Skewness | -0.064891381 | -0.00038955837 |
| Sum | 203934 | 201325 |
| Variance | 65622.467 | 63665.63 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 362 | 1 | 0.2% |
| 529 | 1 | 0.2% |
| 173 | 1 | 0.2% |
| 176 | 1 | 0.2% |
| 521 | 1 | 0.2% |
| 855 | 1 | 0.2% |
| 608 | 1 | 0.2% |
| 767 | 1 | 0.2% |
| 123 | 1 | 0.2% |
| 207 | 1 | 0.2% |
| Other values (436) | 436 |
| Value | Count | Frequency (%) |
| 581 | 1 | 0.2% |
| 244 | 1 | 0.2% |
| 474 | 1 | 0.2% |
| 261 | 1 | 0.2% |
| 396 | 1 | 0.2% |
| 130 | 1 | 0.2% |
| 83 | 1 | 0.2% |
| 836 | 1 | 0.2% |
| 348 | 1 | 0.2% |
| 683 | 1 | 0.2% |
| Other values (436) | 436 |
| Value | Count | Frequency (%) |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 12 | 1 | |
| 16 | 1 | |
| 17 | 1 |
| Value | Count | Frequency (%) |
| 2 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 10 | 1 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 1 | |
| 19 | 1 | |
| 24 | 1 |
| Value | Count | Frequency (%) |
| 2 | 1 | |
| 6 | 1 | |
| 7 | 1 | |
| 10 | 1 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 1 | |
| 19 | 1 | |
| 24 | 1 |
| Value | Count | Frequency (%) |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 12 | 1 | |
| 16 | 1 | |
| 17 | 1 |
Survived
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 2 | 2 |
| Distinct (%) | 0.4% | 0.4% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
| 0 | |
|---|---|
| 1 |
| 0 | |
|---|---|
| 1 |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 1 | 1 |
| Median length | 1 | 1 |
| Mean length | 1 | 1 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 446 | 446 |
| Distinct characters | 2 | 2 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | 0 | 1 |
| 2nd row | 0 | 1 |
| 3rd row | 0 | 0 |
| 4th row | 1 | 0 |
| 5th row | 0 | 0 |
Common Values
| Value | Count | Frequency (%) |
| 0 | 286 | |
| 1 | 160 |
| Value | Count | Frequency (%) |
| 0 | 272 | |
| 1 | 174 |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| 0 | 286 | |
| 1 | 160 |
| Value | Count | Frequency (%) |
| 0 | 272 | |
| 1 | 174 |
Most occurring characters
| Value | Count | Frequency (%) |
| 0 | 286 | |
| 1 | 160 |
| Value | Count | Frequency (%) |
| 0 | 272 | |
| 1 | 174 |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 446 |
| Value | Count | Frequency (%) |
| Decimal Number | 446 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 0 | 286 | |
| 1 | 160 |
| Value | Count | Frequency (%) |
| 0 | 272 | |
| 1 | 174 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 446 |
| Value | Count | Frequency (%) |
| Common | 446 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 0 | 286 | |
| 1 | 160 |
| Value | Count | Frequency (%) |
| 0 | 272 | |
| 1 | 174 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 446 |
| Value | Count | Frequency (%) |
| ASCII | 446 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 0 | 286 | |
| 1 | 160 |
| Value | Count | Frequency (%) |
| 0 | 272 | |
| 1 | 174 |
Pclass
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 3 | 3 |
| Distinct (%) | 0.7% | 0.7% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
| 3 | |
|---|---|
| 2 | |
| 1 |
| 3 | |
|---|---|
| 1 | |
| 2 |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 1 | 1 |
| Median length | 1 | 1 |
| Mean length | 1 | 1 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 446 | 446 |
| Distinct characters | 3 | 3 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | 2 | 2 |
| 2nd row | 2 | 2 |
| 3rd row | 2 | 3 |
| 4th row | 3 | 1 |
| 5th row | 3 | 3 |
Common Values
| Value | Count | Frequency (%) |
| 3 | 263 | |
| 2 | 96 | 21.5% |
| 1 | 87 | 19.5% |
| Value | Count | Frequency (%) |
| 3 | 255 | |
| 1 | 101 | 22.6% |
| 2 | 90 | 20.2% |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| 3 | 263 | |
| 2 | 96 | 21.5% |
| 1 | 87 | 19.5% |
| Value | Count | Frequency (%) |
| 3 | 255 | |
| 1 | 101 | 22.6% |
| 2 | 90 | 20.2% |
Most occurring characters
| Value | Count | Frequency (%) |
| 3 | 263 | |
| 2 | 96 | 21.5% |
| 1 | 87 | 19.5% |
| Value | Count | Frequency (%) |
| 3 | 255 | |
| 1 | 101 | 22.6% |
| 2 | 90 | 20.2% |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 446 |
| Value | Count | Frequency (%) |
| Decimal Number | 446 |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 3 | 263 | |
| 2 | 96 | 21.5% |
| 1 | 87 | 19.5% |
| Value | Count | Frequency (%) |
| 3 | 255 | |
| 1 | 101 | 22.6% |
| 2 | 90 | 20.2% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 446 |
| Value | Count | Frequency (%) |
| Common | 446 |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 3 | 263 | |
| 2 | 96 | 21.5% |
| 1 | 87 | 19.5% |
| Value | Count | Frequency (%) |
| 3 | 255 | |
| 1 | 101 | 22.6% |
| 2 | 90 | 20.2% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 446 |
| Value | Count | Frequency (%) |
| ASCII | 446 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 3 | 263 | |
| 2 | 96 | 21.5% |
| 1 | 87 | 19.5% |
| Value | Count | Frequency (%) |
| 3 | 255 | |
| 1 | 101 | 22.6% |
| 2 | 90 | 20.2% |
Name
['Text', 'Text']
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 446 | 446 |
| Distinct (%) | 100.0% | 100.0% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 82 | 82 |
| Median length | 50 | 51 |
| Mean length | 26.838565 | 26.699552 |
| Min length | 12 | 12 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 11970 | 11908 |
| Distinct characters | 59 | 58 |
| Distinct categories | 7 | 7 ? |
| Distinct scripts | 2 | 2 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 446 | 446 ? |
| Unique (%) | 100.0% | 100.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | del Carlo, Mr. Sebastiano | Christy, Miss. Julie Rachel |
| 2nd row | Givard, Mr. Hans Kristensen | Brown, Miss. Amelia "Mildred" |
| 3rd row | Hold, Mr. Stephen | Meek, Mrs. Thomas (Annie Louise Rowley) |
| 4th row | Goldsmith, Mrs. Frank John (Emily Alice Brown) | Newell, Mr. Arthur Webster |
| 5th row | Panula, Mr. Jaako Arnold | Ford, Mr. William Neal |
| Value | Count | Frequency (%) |
| mr | 269 | 14.8% |
| miss | 84 | 4.6% |
| mrs | 68 | 3.7% |
| william | 27 | 1.5% |
| john | 24 | 1.3% |
| master | 19 | 1.0% |
| henry | 17 | 0.9% |
| george | 14 | 0.8% |
| james | 13 | 0.7% |
| mary | 13 | 0.7% |
| Other values (887) | 1272 |
| Value | Count | Frequency (%) |
| mr | 259 | 14.3% |
| miss | 92 | 5.1% |
| mrs | 66 | 3.6% |
| william | 29 | 1.6% |
| john | 22 | 1.2% |
| master | 18 | 1.0% |
| henry | 14 | 0.8% |
| james | 13 | 0.7% |
| thomas | 13 | 0.7% |
| charles | 10 | 0.6% |
| Other values (903) | 1276 |
Most occurring characters
| Value | Count | Frequency (%) |
| 1376 | 11.5% | |
| r | 1007 | 8.4% |
| e | 848 | 7.1% |
| a | 811 | 6.8% |
| i | 660 | 5.5% |
| n | 641 | 5.4% |
| s | 629 | 5.3% |
| M | 553 | 4.6% |
| l | 522 | 4.4% |
| o | 504 | 4.2% |
| Other values (49) | 4419 |
| Value | Count | Frequency (%) |
| 1368 | 11.5% | |
| r | 942 | 7.9% |
| a | 852 | 7.2% |
| e | 824 | 6.9% |
| s | 662 | 5.6% |
| i | 652 | 5.5% |
| n | 638 | 5.4% |
| M | 576 | 4.8% |
| l | 511 | 4.3% |
| o | 505 | 4.2% |
| Other values (48) | 4378 |
Most occurring categories
| Value | Count | Frequency (%) |
| Lowercase Letter | 7648 | |
| Uppercase Letter | 1823 | 15.2% |
| Space Separator | 1376 | 11.5% |
| Other Punctuation | 962 | 8.0% |
| Open Punctuation | 79 | 0.7% |
| Close Punctuation | 79 | 0.7% |
| Dash Punctuation | 3 | < 0.1% |
| Value | Count | Frequency (%) |
| Lowercase Letter | 7608 | |
| Uppercase Letter | 1824 | 15.3% |
| Space Separator | 1368 | 11.5% |
| Other Punctuation | 954 | 8.0% |
| Open Punctuation | 73 | 0.6% |
| Close Punctuation | 73 | 0.6% |
| Dash Punctuation | 8 | 0.1% |
Most frequent character per category
Space Separator
| Value | Count | Frequency (%) |
| 1376 |
| Value | Count | Frequency (%) |
| 1368 |
Lowercase Letter
| Value | Count | Frequency (%) |
| r | 1007 | |
| e | 848 | |
| a | 811 | |
| i | 660 | |
| n | 641 | |
| s | 629 | |
| l | 522 | 6.8% |
| o | 504 | 6.6% |
| t | 343 | 4.5% |
| h | 256 | 3.3% |
| Other values (16) | 1427 |
| Value | Count | Frequency (%) |
| r | 942 | |
| a | 852 | |
| e | 824 | |
| s | 662 | |
| i | 652 | |
| n | 638 | |
| l | 511 | 6.7% |
| o | 505 | 6.6% |
| t | 315 | 4.1% |
| h | 252 | 3.3% |
| Other values (16) | 1455 |
Uppercase Letter
| Value | Count | Frequency (%) |
| M | 553 | |
| J | 116 | 6.4% |
| A | 113 | 6.2% |
| H | 99 | 5.4% |
| C | 90 | 4.9% |
| E | 89 | 4.9% |
| S | 87 | 4.8% |
| W | 70 | 3.8% |
| B | 69 | 3.8% |
| L | 66 | 3.6% |
| Other values (15) | 471 |
| Value | Count | Frequency (%) |
| M | 576 | |
| A | 115 | 6.3% |
| J | 113 | 6.2% |
| H | 97 | 5.3% |
| S | 94 | 5.2% |
| C | 91 | 5.0% |
| E | 82 | 4.5% |
| B | 77 | 4.2% |
| W | 66 | 3.6% |
| L | 61 | 3.3% |
| Other values (14) | 452 |
Other Punctuation
| Value | Count | Frequency (%) |
| , | 446 | |
| . | 446 | |
| " | 66 | 6.9% |
| ' | 4 | 0.4% |
| Value | Count | Frequency (%) |
| , | 446 | |
| . | 446 | |
| " | 54 | 5.7% |
| ' | 8 | 0.8% |
Open Punctuation
| Value | Count | Frequency (%) |
| ( | 79 |
| Value | Count | Frequency (%) |
| ( | 73 |
Close Punctuation
| Value | Count | Frequency (%) |
| ) | 79 |
| Value | Count | Frequency (%) |
| ) | 73 |
Dash Punctuation
| Value | Count | Frequency (%) |
| - | 3 |
| Value | Count | Frequency (%) |
| - | 8 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Latin | 9471 | |
| Common | 2499 | 20.9% |
| Value | Count | Frequency (%) |
| Latin | 9432 | |
| Common | 2476 | 20.8% |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 1376 | ||
| , | 446 | 17.8% |
| . | 446 | 17.8% |
| ( | 79 | 3.2% |
| ) | 79 | 3.2% |
| " | 66 | 2.6% |
| ' | 4 | 0.2% |
| - | 3 | 0.1% |
| Value | Count | Frequency (%) |
| 1368 | ||
| , | 446 | 18.0% |
| . | 446 | 18.0% |
| ( | 73 | 2.9% |
| ) | 73 | 2.9% |
| " | 54 | 2.2% |
| - | 8 | 0.3% |
| ' | 8 | 0.3% |
Latin
| Value | Count | Frequency (%) |
| r | 1007 | 10.6% |
| e | 848 | 9.0% |
| a | 811 | 8.6% |
| i | 660 | 7.0% |
| n | 641 | 6.8% |
| s | 629 | 6.6% |
| M | 553 | 5.8% |
| l | 522 | 5.5% |
| o | 504 | 5.3% |
| t | 343 | 3.6% |
| Other values (41) | 2953 |
| Value | Count | Frequency (%) |
| r | 942 | 10.0% |
| a | 852 | 9.0% |
| e | 824 | 8.7% |
| s | 662 | 7.0% |
| i | 652 | 6.9% |
| n | 638 | 6.8% |
| M | 576 | 6.1% |
| l | 511 | 5.4% |
| o | 505 | 5.4% |
| t | 315 | 3.3% |
| Other values (40) | 2955 |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 11970 |
| Value | Count | Frequency (%) |
| ASCII | 11908 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 1376 | 11.5% | |
| r | 1007 | 8.4% |
| e | 848 | 7.1% |
| a | 811 | 6.8% |
| i | 660 | 5.5% |
| n | 641 | 5.4% |
| s | 629 | 5.3% |
| M | 553 | 4.6% |
| l | 522 | 4.4% |
| o | 504 | 4.2% |
| Other values (49) | 4419 |
| Value | Count | Frequency (%) |
| 1368 | 11.5% | |
| r | 942 | 7.9% |
| a | 852 | 7.2% |
| e | 824 | 6.9% |
| s | 662 | 5.6% |
| i | 652 | 5.5% |
| n | 638 | 5.4% |
| M | 576 | 4.8% |
| l | 511 | 4.3% |
| o | 505 | 4.2% |
| Other values (48) | 4378 |
Sex
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 2 | 2 |
| Distinct (%) | 0.4% | 0.4% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
| male | |
|---|---|
| female |
| male | |
|---|---|
| female |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 6 | 6 |
| Median length | 4 | 4 |
| Mean length | 4.6726457 | 4.7174888 |
| Min length | 4 | 4 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 2084 | 2104 |
| Distinct characters | 5 | 5 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | male | female |
| 2nd row | male | female |
| 3rd row | male | female |
| 4th row | female | male |
| 5th row | male | male |
Common Values
| Value | Count | Frequency (%) |
| male | 296 | |
| female | 150 |
| Value | Count | Frequency (%) |
| male | 286 | |
| female | 160 |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| male | 296 | |
| female | 150 |
| Value | Count | Frequency (%) |
| male | 286 | |
| female | 160 |
Most occurring characters
| Value | Count | Frequency (%) |
| e | 596 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 150 | 7.2% |
| Value | Count | Frequency (%) |
| e | 606 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 160 | 7.6% |
Most occurring categories
| Value | Count | Frequency (%) |
| Lowercase Letter | 2084 |
| Value | Count | Frequency (%) |
| Lowercase Letter | 2104 |
Most frequent character per category
Lowercase Letter
| Value | Count | Frequency (%) |
| e | 596 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 150 | 7.2% |
| Value | Count | Frequency (%) |
| e | 606 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 160 | 7.6% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Latin | 2084 |
| Value | Count | Frequency (%) |
| Latin | 2104 |
Most frequent character per script
Latin
| Value | Count | Frequency (%) |
| e | 596 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 150 | 7.2% |
| Value | Count | Frequency (%) |
| e | 606 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 160 | 7.6% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 2084 |
| Value | Count | Frequency (%) |
| ASCII | 2104 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| e | 596 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 150 | 7.2% |
| Value | Count | Frequency (%) |
| e | 606 | |
| m | 446 | |
| a | 446 | |
| l | 446 | |
| f | 160 | 7.6% |
Age
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 73 | 77 |
| Distinct (%) | 20.3% | 21.4% |
| Missing | 86 | 87 |
| Missing (%) | 19.3% | 19.5% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 30.095833 | 29.697772 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0.67 | 0.42 |
| Maximum | 71 | 71 |
| Zeros | 0 | 0 |
| Zeros (%) | 0.0% | 0.0% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0.67 | 0.42 |
| 5-th percentile | 4 | 4.9 |
| Q1 | 21 | 20.75 |
| median | 30 | 28 |
| Q3 | 39 | 38 |
| 95-th percentile | 55.525 | 56 |
| Maximum | 71 | 71 |
| Range | 70.33 | 70.58 |
| Interquartile range (IQR) | 18 | 17.25 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 14.084735 | 14.367229 |
| Coefficient of variation (CV) | 0.46799617 | 0.48378139 |
| Kurtosis | 0.15019465 | 0.049728962 |
| Mean | 30.095833 | 29.697772 |
| Median Absolute Deviation (MAD) | 9 | 9 |
| Skewness | 0.29235308 | 0.39198147 |
| Sum | 10834.5 | 10661.5 |
| Variance | 198.37975 | 206.41728 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 36 | 15 | 3.4% |
| 19 | 14 | 3.1% |
| 30 | 14 | 3.1% |
| 18 | 14 | 3.1% |
| 22 | 13 | 2.9% |
| 31 | 12 | 2.7% |
| 27 | 12 | 2.7% |
| 32 | 12 | 2.7% |
| 24 | 11 | 2.5% |
| 40 | 10 | 2.2% |
| Other values (63) | 233 | |
| (Missing) | 86 | 19.3% |
| Value | Count | Frequency (%) |
| 24 | 19 | 4.3% |
| 21 | 16 | 3.6% |
| 22 | 16 | 3.6% |
| 18 | 14 | 3.1% |
| 19 | 13 | 2.9% |
| 36 | 13 | 2.9% |
| 32 | 12 | 2.7% |
| 30 | 12 | 2.7% |
| 28 | 11 | 2.5% |
| 29 | 10 | 2.2% |
| Other values (67) | 223 | |
| (Missing) | 87 | 19.5% |
| Value | Count | Frequency (%) |
| 0.67 | 1 | 0.2% |
| 0.83 | 1 | 0.2% |
| 1 | 3 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 5 | |
| 5 | 1 | 0.2% |
| 6 | 2 | 0.4% |
| 7 | 1 | 0.2% |
| 8 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0.42 | 1 | 0.2% |
| 0.75 | 1 | 0.2% |
| 0.83 | 1 | 0.2% |
| 1 | 3 | |
| 2 | 4 | |
| 3 | 2 | 0.4% |
| 4 | 6 | |
| 5 | 2 | 0.4% |
| 6 | 1 | 0.2% |
| 7 | 3 |
| Value | Count | Frequency (%) |
| 0.42 | 1 | 0.2% |
| 0.75 | 1 | 0.2% |
| 0.83 | 1 | 0.2% |
| 1 | 3 | |
| 2 | 4 | |
| 3 | 2 | 0.4% |
| 4 | 6 | |
| 5 | 2 | 0.4% |
| 6 | 1 | 0.2% |
| 7 | 3 |
| Value | Count | Frequency (%) |
| 0.67 | 1 | 0.2% |
| 0.83 | 1 | 0.2% |
| 1 | 3 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 5 | |
| 5 | 1 | 0.2% |
| 6 | 2 | 0.4% |
| 7 | 1 | 0.2% |
| 8 | 1 | 0.2% |
SibSp
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 7 | 7 |
| Distinct (%) | 1.6% | 1.6% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 0.55829596 | 0.50224215 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| Maximum | 8 | 8 |
| Zeros | 297 | 312 |
| Zeros (%) | 66.6% | 70.0% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| 5-th percentile | 0 | 0 |
| Q1 | 0 | 0 |
| median | 0 | 0 |
| Q3 | 1 | 1 |
| 95-th percentile | 3 | 2 |
| Maximum | 8 | 8 |
| Range | 8 | 8 |
| Interquartile range (IQR) | 1 | 1 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 1.1727087 | 1.1112274 |
| Coefficient of variation (CV) | 2.1005143 | 2.2125332 |
| Kurtosis | 18.271441 | 19.597753 |
| Mean | 0.55829596 | 0.50224215 |
| Median Absolute Deviation (MAD) | 0 | 0 |
| Skewness | 3.7852073 | 3.8980696 |
| Sum | 249 | 224 |
| Variance | 1.3752456 | 1.2348264 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=7)
| Value | Count | Frequency (%) |
| 0 | 297 | |
| 1 | 111 | 24.9% |
| 2 | 13 | 2.9% |
| 3 | 10 | 2.2% |
| 4 | 8 | 1.8% |
| 8 | 5 | 1.1% |
| 5 | 2 | 0.4% |
| Value | Count | Frequency (%) |
| 0 | 312 | |
| 1 | 98 | 22.0% |
| 2 | 15 | 3.4% |
| 4 | 9 | 2.0% |
| 3 | 6 | 1.3% |
| 8 | 4 | 0.9% |
| 5 | 2 | 0.4% |
| Value | Count | Frequency (%) |
| 0 | 297 | |
| 1 | 111 | 24.9% |
| 2 | 13 | 2.9% |
| 3 | 10 | 2.2% |
| 4 | 8 | 1.8% |
| 5 | 2 | 0.4% |
| 8 | 5 | 1.1% |
| Value | Count | Frequency (%) |
| 0 | 312 | |
| 1 | 98 | 22.0% |
| 2 | 15 | 3.4% |
| 3 | 6 | 1.3% |
| 4 | 9 | 2.0% |
| 5 | 2 | 0.4% |
| 8 | 4 | 0.9% |
| Value | Count | Frequency (%) |
| 0 | 312 | |
| 1 | 98 | 22.0% |
| 2 | 15 | 3.4% |
| 3 | 6 | 1.3% |
| 4 | 9 | 2.0% |
| 5 | 2 | 0.4% |
| 8 | 4 | 0.9% |
| Value | Count | Frequency (%) |
| 0 | 297 | |
| 1 | 111 | 24.9% |
| 2 | 13 | 2.9% |
| 3 | 10 | 2.2% |
| 4 | 8 | 1.8% |
| 5 | 2 | 0.4% |
| 8 | 5 | 1.1% |
Parch
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 7 | 6 |
| Distinct (%) | 1.6% | 1.3% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 0.38565022 | 0.37668161 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| Maximum | 6 | 5 |
| Zeros | 339 | 344 |
| Zeros (%) | 76.0% | 77.1% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| 5-th percentile | 0 | 0 |
| Q1 | 0 | 0 |
| median | 0 | 0 |
| Q3 | 0 | 0 |
| 95-th percentile | 2 | 2 |
| Maximum | 6 | 5 |
| Range | 6 | 5 |
| Interquartile range (IQR) | 0 | 0 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 0.83419633 | 0.81380986 |
| Coefficient of variation (CV) | 2.1630905 | 2.1604714 |
| Kurtosis | 11.541467 | 9.4840994 |
| Mean | 0.38565022 | 0.37668161 |
| Median Absolute Deviation (MAD) | 0 | 0 |
| Skewness | 2.9792018 | 2.7521166 |
| Sum | 172 | 168 |
| Variance | 0.69588351 | 0.66228649 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=7)
| Value | Count | Frequency (%) |
| 0 | 339 | |
| 1 | 62 | 13.9% |
| 2 | 36 | 8.1% |
| 5 | 3 | 0.7% |
| 3 | 3 | 0.7% |
| 4 | 2 | 0.4% |
| 6 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 344 | |
| 1 | 52 | 11.7% |
| 2 | 43 | 9.6% |
| 5 | 4 | 0.9% |
| 3 | 2 | 0.4% |
| 4 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 339 | |
| 1 | 62 | 13.9% |
| 2 | 36 | 8.1% |
| 3 | 3 | 0.7% |
| 4 | 2 | 0.4% |
| 5 | 3 | 0.7% |
| 6 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 344 | |
| 1 | 52 | 11.7% |
| 2 | 43 | 9.6% |
| 3 | 2 | 0.4% |
| 4 | 1 | 0.2% |
| 5 | 4 | 0.9% |
| Value | Count | Frequency (%) |
| 0 | 344 | |
| 1 | 52 | 11.7% |
| 2 | 43 | 9.6% |
| 3 | 2 | 0.4% |
| 4 | 1 | 0.2% |
| 5 | 4 | 0.9% |
| Value | Count | Frequency (%) |
| 0 | 339 | |
| 1 | 62 | 13.9% |
| 2 | 36 | 8.1% |
| 3 | 3 | 0.7% |
| 4 | 2 | 0.4% |
| 5 | 3 | 0.7% |
| 6 | 1 | 0.2% |
Ticket
['Text', 'Text']
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 377 | 386 |
| Distinct (%) | 84.5% | 86.5% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 18 | 18 |
| Median length | 17 | 17 |
| Mean length | 6.896861 | 6.7152466 |
| Min length | 3 | 3 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 3076 | 2995 |
| Distinct characters | 35 | 35 |
| Distinct categories | 5 | 5 ? |
| Distinct scripts | 2 | 2 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 326 | 341 ? |
| Unique (%) | 73.1% | 76.5% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | SC/PARIS 2167 | 237789 |
| 2nd row | 250646 | 248733 |
| 3rd row | 26707 | 343095 |
| 4th row | 363291 | 35273 |
| 5th row | 3101295 | W./C. 6608 |
| Value | Count | Frequency (%) |
| pc | 23 | 4.0% |
| c.a | 13 | 2.3% |
| a/5 | 10 | 1.8% |
| 2 | 8 | 1.4% |
| ca | 8 | 1.4% |
| ston/o | 8 | 1.4% |
| 1601 | 6 | 1.1% |
| soton/o.q | 5 | 0.9% |
| a/4 | 5 | 0.9% |
| 2343 | 5 | 0.9% |
| Other values (398) | 479 |
| Value | Count | Frequency (%) |
| pc | 32 | 5.6% |
| c.a | 11 | 1.9% |
| a/5 | 10 | 1.8% |
| ston/o | 7 | 1.2% |
| 2 | 7 | 1.2% |
| ca | 6 | 1.1% |
| 347082 | 5 | 0.9% |
| 1601 | 5 | 0.9% |
| w./c | 5 | 0.9% |
| soton/o.q | 4 | 0.7% |
| Other values (410) | 476 |
Most occurring characters
| Value | Count | Frequency (%) |
| 3 | 392 | |
| 1 | 333 | |
| 2 | 313 | |
| 4 | 252 | 8.2% |
| 7 | 235 | 7.6% |
| 0 | 213 | 6.9% |
| 6 | 201 | 6.5% |
| 5 | 188 | 6.1% |
| 9 | 163 | 5.3% |
| 8 | 147 | 4.8% |
| Other values (25) | 639 |
| Value | Count | Frequency (%) |
| 3 | 380 | |
| 1 | 317 | |
| 2 | 286 | |
| 7 | 250 | |
| 4 | 225 | 7.5% |
| 6 | 225 | 7.5% |
| 0 | 216 | 7.2% |
| 5 | 208 | 6.9% |
| 9 | 142 | 4.7% |
| 8 | 141 | 4.7% |
| Other values (25) | 605 |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 2437 | |
| Uppercase Letter | 344 | 11.2% |
| Other Punctuation | 162 | 5.3% |
| Space Separator | 124 | 4.0% |
| Lowercase Letter | 9 | 0.3% |
| Value | Count | Frequency (%) |
| Decimal Number | 2390 | |
| Uppercase Letter | 323 | 10.8% |
| Other Punctuation | 148 | 4.9% |
| Space Separator | 122 | 4.1% |
| Lowercase Letter | 12 | 0.4% |
Most frequent character per category
Decimal Number
| Value | Count | Frequency (%) |
| 3 | 392 | |
| 1 | 333 | |
| 2 | 313 | |
| 4 | 252 | |
| 7 | 235 | |
| 0 | 213 | |
| 6 | 201 | |
| 5 | 188 | |
| 9 | 163 | |
| 8 | 147 | 6.0% |
| Value | Count | Frequency (%) |
| 3 | 380 | |
| 1 | 317 | |
| 2 | 286 | |
| 7 | 250 | |
| 4 | 225 | |
| 6 | 225 | |
| 0 | 216 | |
| 5 | 208 | |
| 9 | 142 | 5.9% |
| 8 | 141 | 5.9% |
Space Separator
| Value | Count | Frequency (%) |
| 124 |
| Value | Count | Frequency (%) |
| 122 |
Other Punctuation
| Value | Count | Frequency (%) |
| . | 106 | |
| / | 56 |
| Value | Count | Frequency (%) |
| . | 98 | |
| / | 50 |
Uppercase Letter
| Value | Count | Frequency (%) |
| C | 67 | |
| O | 64 | |
| A | 45 | |
| S | 42 | |
| P | 39 | |
| N | 26 | 7.6% |
| T | 24 | 7.0% |
| Q | 9 | 2.6% |
| W | 8 | 2.3% |
| I | 5 | 1.5% |
| Other values (6) | 15 | 4.4% |
| Value | Count | Frequency (%) |
| C | 76 | |
| P | 49 | |
| O | 49 | |
| A | 40 | |
| S | 37 | |
| N | 20 | 6.2% |
| T | 18 | 5.6% |
| W | 8 | 2.5% |
| Q | 7 | 2.2% |
| I | 5 | 1.5% |
| Other values (6) | 14 | 4.3% |
Lowercase Letter
| Value | Count | Frequency (%) |
| a | 3 | |
| s | 2 | |
| l | 1 | 11.1% |
| e | 1 | 11.1% |
| r | 1 | 11.1% |
| i | 1 | 11.1% |
| Value | Count | Frequency (%) |
| a | 3 | |
| s | 3 | |
| r | 2 | |
| i | 2 | |
| l | 1 | 8.3% |
| e | 1 | 8.3% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 2723 | |
| Latin | 353 | 11.5% |
| Value | Count | Frequency (%) |
| Common | 2660 | |
| Latin | 335 | 11.2% |
Most frequent character per script
Common
| Value | Count | Frequency (%) |
| 3 | 392 | |
| 1 | 333 | |
| 2 | 313 | |
| 4 | 252 | |
| 7 | 235 | |
| 0 | 213 | |
| 6 | 201 | |
| 5 | 188 | |
| 9 | 163 | |
| 8 | 147 | 5.4% |
| Other values (3) | 286 |
| Value | Count | Frequency (%) |
| 3 | 380 | |
| 1 | 317 | |
| 2 | 286 | |
| 7 | 250 | |
| 4 | 225 | |
| 6 | 225 | |
| 0 | 216 | |
| 5 | 208 | |
| 9 | 142 | 5.3% |
| 8 | 141 | 5.3% |
| Other values (3) | 270 |
Latin
| Value | Count | Frequency (%) |
| C | 67 | |
| O | 64 | |
| A | 45 | |
| S | 42 | |
| P | 39 | |
| N | 26 | 7.4% |
| T | 24 | 6.8% |
| Q | 9 | 2.5% |
| W | 8 | 2.3% |
| I | 5 | 1.4% |
| Other values (12) | 24 | 6.8% |
| Value | Count | Frequency (%) |
| C | 76 | |
| P | 49 | |
| O | 49 | |
| A | 40 | |
| S | 37 | |
| N | 20 | 6.0% |
| T | 18 | 5.4% |
| W | 8 | 2.4% |
| Q | 7 | 2.1% |
| I | 5 | 1.5% |
| Other values (12) | 26 | 7.8% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 3076 |
| Value | Count | Frequency (%) |
| ASCII | 2995 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| 3 | 392 | |
| 1 | 333 | |
| 2 | 313 | |
| 4 | 252 | 8.2% |
| 7 | 235 | 7.6% |
| 0 | 213 | 6.9% |
| 6 | 201 | 6.5% |
| 5 | 188 | 6.1% |
| 9 | 163 | 5.3% |
| 8 | 147 | 4.8% |
| Other values (25) | 639 |
| Value | Count | Frequency (%) |
| 3 | 380 | |
| 1 | 317 | |
| 2 | 286 | |
| 7 | 250 | |
| 4 | 225 | 7.5% |
| 6 | 225 | 7.5% |
| 0 | 216 | 7.2% |
| 5 | 208 | 6.9% |
| 9 | 142 | 4.7% |
| 8 | 141 | 4.7% |
| Other values (25) | 605 |
Fare
Real number (ℝ)
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 171 | 180 |
| Distinct (%) | 38.3% | 40.4% |
| Missing | 0 | 0 |
| Missing (%) | 0.0% | 0.0% |
| Infinite | 0 | 0 |
| Infinite (%) | 0.0% | 0.0% |
| Mean | 29.631267 | 31.612088 |
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| Maximum | 512.3292 | 512.3292 |
| Zeros | 4 | 5 |
| Zeros (%) | 0.9% | 1.1% |
| Negative | 0 | 0 |
| Negative (%) | 0.0% | 0.0% |
| Memory size | 7.0 KiB | 7.0 KiB |
Quantile statistics
| Dataset A | Dataset B | |
|---|---|---|
| Minimum | 0 | 0 |
| 5-th percentile | 7.15 | 7.225 |
| Q1 | 7.925 | 7.925 |
| median | 14.4542 | 14.4542 |
| Q3 | 29.125 | 30.5 |
| 95-th percentile | 90 | 106.425 |
| Maximum | 512.3292 | 512.3292 |
| Range | 512.3292 | 512.3292 |
| Interquartile range (IQR) | 21.2 | 22.575 |
Descriptive statistics
| Dataset A | Dataset B | |
|---|---|---|
| Standard deviation | 48.123386 | 53.362892 |
| Coefficient of variation (CV) | 1.6240745 | 1.6880533 |
| Kurtosis | 48.501181 | 45.197189 |
| Mean | 29.631267 | 31.612088 |
| Median Absolute Deviation (MAD) | 6.76255 | 6.7167 |
| Skewness | 5.9002012 | 5.8543282 |
| Sum | 13215.545 | 14098.991 |
| Variance | 2315.8603 | 2847.5982 |
| Monotonicity | Not monotonic | Not monotonic |
Histogram with fixed size bins (bins=50)
| Value | Count | Frequency (%) |
| 8.05 | 26 | 5.8% |
| 26 | 22 | 4.9% |
| 7.8958 | 18 | 4.0% |
| 13 | 17 | 3.8% |
| 7.75 | 17 | 3.8% |
| 7.925 | 14 | 3.1% |
| 10.5 | 13 | 2.9% |
| 7.225 | 8 | 1.8% |
| 26.55 | 8 | 1.8% |
| 7.25 | 7 | 1.6% |
| Other values (161) | 296 |
| Value | Count | Frequency (%) |
| 8.05 | 21 | 4.7% |
| 13 | 20 | 4.5% |
| 7.75 | 20 | 4.5% |
| 26 | 17 | 3.8% |
| 7.8958 | 15 | 3.4% |
| 10.5 | 11 | 2.5% |
| 7.2292 | 10 | 2.2% |
| 7.775 | 9 | 2.0% |
| 26.55 | 8 | 1.8% |
| 7.8542 | 8 | 1.8% |
| Other values (170) | 307 |
| Value | Count | Frequency (%) |
| 0 | 4 | |
| 4.0125 | 1 | 0.2% |
| 5 | 1 | 0.2% |
| 6.2375 | 1 | 0.2% |
| 6.45 | 1 | 0.2% |
| 6.4958 | 2 | |
| 6.75 | 1 | 0.2% |
| 6.8583 | 1 | 0.2% |
| 6.95 | 1 | 0.2% |
| 6.975 | 1 | 0.2% |
| Value | Count | Frequency (%) |
| 0 | 5 | |
| 4.0125 | 1 | 0.2% |
| 6.2375 | 1 | 0.2% |
| 6.4375 | 1 | 0.2% |
| 6.45 | 1 | 0.2% |
| 6.4958 | 1 | 0.2% |
| 6.75 | 1 | 0.2% |
| 6.975 | 1 | 0.2% |
| 7.0458 | 1 | 0.2% |
| 7.05 | 2 | 0.4% |
| Value | Count | Frequency (%) |
| 0 | 5 | |
| 4.0125 | 1 | 0.2% |
| 6.2375 | 1 | 0.2% |
| 6.4375 | 1 | 0.2% |
| 6.45 | 1 | 0.2% |
| 6.4958 | 1 | 0.2% |
| 6.75 | 1 | 0.2% |
| 6.975 | 1 | 0.2% |
| 7.0458 | 1 | 0.2% |
| 7.05 | 2 | 0.4% |
| Value | Count | Frequency (%) |
| 0 | 4 | |
| 4.0125 | 1 | 0.2% |
| 5 | 1 | 0.2% |
| 6.2375 | 1 | 0.2% |
| 6.45 | 1 | 0.2% |
| 6.4958 | 2 | |
| 6.75 | 1 | 0.2% |
| 6.8583 | 1 | 0.2% |
| 6.95 | 1 | 0.2% |
| 6.975 | 1 | 0.2% |
Cabin
['Text', 'Text']
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 72 | 88 |
| Distinct (%) | 85.7% | 87.1% |
| Missing | 362 | 345 |
| Missing (%) | 81.2% | 77.4% |
| Memory size | 7.0 KiB | 7.0 KiB |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 11 | 15 |
| Median length | 3 | 3 |
| Mean length | 3.4761905 | 3.3069307 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 292 | 334 |
| Distinct characters | 18 | 18 |
| Distinct categories | 3 | 3 ? |
| Distinct scripts | 2 | 2 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 61 | 78 ? |
| Unique (%) | 72.6% | 77.2% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | B80 | F33 |
| 2nd row | C92 | D48 |
| 3rd row | E121 | C90 |
| 4th row | C30 | B28 |
| 5th row | C123 | B51 B53 B55 |
| Value | Count | Frequency (%) |
| f2 | 3 | 3.1% |
| b51 | 2 | 2.1% |
| e33 | 2 | 2.1% |
| e121 | 2 | 2.1% |
| c25 | 2 | 2.1% |
| c23 | 2 | 2.1% |
| e8 | 2 | 2.1% |
| b55 | 2 | 2.1% |
| b53 | 2 | 2.1% |
| c27 | 2 | 2.1% |
| Other values (69) | 76 |
| Value | Count | Frequency (%) |
| g6 | 3 | 2.7% |
| f2 | 3 | 2.7% |
| d | 3 | 2.7% |
| e33 | 2 | 1.8% |
| b28 | 2 | 1.8% |
| e101 | 2 | 1.8% |
| c65 | 2 | 1.8% |
| c125 | 2 | 1.8% |
| b35 | 2 | 1.8% |
| e44 | 2 | 1.8% |
| Other values (87) | 87 |
Most occurring characters
| Value | Count | Frequency (%) |
| C | 28 | 9.6% |
| 2 | 27 | 9.2% |
| 1 | 27 | 9.2% |
| 3 | 26 | 8.9% |
| B | 24 | 8.2% |
| 6 | 16 | 5.5% |
| 5 | 16 | 5.5% |
| 8 | 16 | 5.5% |
| 7 | 16 | 5.5% |
| 0 | 15 | 5.1% |
| Other values (8) | 81 |
| Value | Count | Frequency (%) |
| 1 | 34 | 10.2% |
| C | 27 | 8.1% |
| 5 | 25 | 7.5% |
| 2 | 25 | 7.5% |
| B | 24 | 7.2% |
| 6 | 24 | 7.2% |
| 4 | 23 | 6.9% |
| E | 22 | 6.6% |
| 3 | 22 | 6.6% |
| 8 | 21 | 6.3% |
| Other values (8) | 87 |
Most occurring categories
| Value | Count | Frequency (%) |
| Decimal Number | 182 | |
| Uppercase Letter | 97 | |
| Space Separator | 13 | 4.5% |
| Value | Count | Frequency (%) |
| Decimal Number | 215 | |
| Uppercase Letter | 110 | |
| Space Separator | 9 | 2.7% |
Most frequent character per category
Uppercase Letter
| Value | Count | Frequency (%) |
| C | 28 | |
| B | 24 | |
| E | 15 | |
| D | 13 | |
| F | 8 | 8.2% |
| A | 6 | 6.2% |
| G | 3 | 3.1% |
| Value | Count | Frequency (%) |
| C | 27 | |
| B | 24 | |
| E | 22 | |
| D | 19 | |
| A | 9 | 8.2% |
| F | 6 | 5.5% |
| G | 3 | 2.7% |
Decimal Number
| Value | Count | Frequency (%) |
| 2 | 27 | |
| 1 | 27 | |
| 3 | 26 | |
| 6 | 16 | |
| 5 | 16 | |
| 8 | 16 | |
| 7 | 16 | |
| 0 | 15 | |
| 9 | 12 | |
| 4 | 11 |
| Value | Count | Frequency (%) |
| 1 | 34 | |
| 5 | 25 | |
| 2 | 25 | |
| 6 | 24 | |
| 4 | 23 | |
| 3 | 22 | |
| 8 | 21 | |
| 0 | 18 | |
| 7 | 12 | 5.6% |
| 9 | 11 | 5.1% |
Space Separator
| Value | Count | Frequency (%) |
| 13 |
| Value | Count | Frequency (%) |
| 9 |
Most occurring scripts
| Value | Count | Frequency (%) |
| Common | 195 | |
| Latin | 97 |
| Value | Count | Frequency (%) |
| Common | 224 | |
| Latin | 110 |
Most frequent character per script
Latin
| Value | Count | Frequency (%) |
| C | 28 | |
| B | 24 | |
| E | 15 | |
| D | 13 | |
| F | 8 | 8.2% |
| A | 6 | 6.2% |
| G | 3 | 3.1% |
| Value | Count | Frequency (%) |
| C | 27 | |
| B | 24 | |
| E | 22 | |
| D | 19 | |
| A | 9 | 8.2% |
| F | 6 | 5.5% |
| G | 3 | 2.7% |
Common
| Value | Count | Frequency (%) |
| 2 | 27 | |
| 1 | 27 | |
| 3 | 26 | |
| 6 | 16 | |
| 5 | 16 | |
| 8 | 16 | |
| 7 | 16 | |
| 0 | 15 | |
| 13 | ||
| 9 | 12 |
| Value | Count | Frequency (%) |
| 1 | 34 | |
| 5 | 25 | |
| 2 | 25 | |
| 6 | 24 | |
| 4 | 23 | |
| 3 | 22 | |
| 8 | 21 | |
| 0 | 18 | |
| 7 | 12 | 5.4% |
| 9 | 11 | 4.9% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 292 |
| Value | Count | Frequency (%) |
| ASCII | 334 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| C | 28 | 9.6% |
| 2 | 27 | 9.2% |
| 1 | 27 | 9.2% |
| 3 | 26 | 8.9% |
| B | 24 | 8.2% |
| 6 | 16 | 5.5% |
| 5 | 16 | 5.5% |
| 8 | 16 | 5.5% |
| 7 | 16 | 5.5% |
| 0 | 15 | 5.1% |
| Other values (8) | 81 |
| Value | Count | Frequency (%) |
| 1 | 34 | 10.2% |
| C | 27 | 8.1% |
| 5 | 25 | 7.5% |
| 2 | 25 | 7.5% |
| B | 24 | 7.2% |
| 6 | 24 | 7.2% |
| 4 | 23 | 6.9% |
| E | 22 | 6.6% |
| 3 | 22 | 6.6% |
| 8 | 21 | 6.3% |
| Other values (8) | 87 |
Embarked
Categorical
| Dataset A | Dataset B | |
|---|---|---|
| Distinct | 3 | 3 |
| Distinct (%) | 0.7% | 0.7% |
| Missing | 0 | 2 |
| Missing (%) | 0.0% | 0.4% |
| Memory size | 7.0 KiB | 7.0 KiB |
| S | |
|---|---|
| C | |
| Q |
| S | |
|---|---|
| C | |
| Q |
Length
| Dataset A | Dataset B | |
|---|---|---|
| Max length | 1 | 1 |
| Median length | 1 | 1 |
| Mean length | 1 | 1 |
| Min length | 1 | 1 |
Characters and Unicode
| Dataset A | Dataset B | |
|---|---|---|
| Total characters | 446 | 444 |
| Distinct characters | 3 | 3 |
| Distinct categories | 1 | 1 ? |
| Distinct scripts | 1 | 1 ? |
| Distinct blocks | 1 | 1 ? |
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.
Unique
| Dataset A | Dataset B | |
|---|---|---|
| Unique | 0 | 0 ? |
| Unique (%) | 0.0% | 0.0% |
Sample
| Dataset A | Dataset B | |
|---|---|---|
| 1st row | C | S |
| 2nd row | S | S |
| 3rd row | S | S |
| 4th row | S | C |
| 5th row | S | S |
Common Values
| Value | Count | Frequency (%) |
| S | 331 | |
| C | 75 | 16.8% |
| Q | 40 | 9.0% |
| Value | Count | Frequency (%) |
| S | 303 | |
| C | 98 | 22.0% |
| Q | 43 | 9.6% |
| (Missing) | 2 | 0.4% |
Length
Histogram of lengths of the category
Common Values (Plot)
Dataset A
Dataset B
| Value | Count | Frequency (%) |
| s | 331 | |
| c | 75 | 16.8% |
| q | 40 | 9.0% |
| Value | Count | Frequency (%) |
| s | 303 | |
| c | 98 | 22.1% |
| q | 43 | 9.7% |
Most occurring characters
| Value | Count | Frequency (%) |
| S | 331 | |
| C | 75 | 16.8% |
| Q | 40 | 9.0% |
| Value | Count | Frequency (%) |
| S | 303 | |
| C | 98 | 22.1% |
| Q | 43 | 9.7% |
Most occurring categories
| Value | Count | Frequency (%) |
| Uppercase Letter | 446 |
| Value | Count | Frequency (%) |
| Uppercase Letter | 444 |
Most frequent character per category
Uppercase Letter
| Value | Count | Frequency (%) |
| S | 331 | |
| C | 75 | 16.8% |
| Q | 40 | 9.0% |
| Value | Count | Frequency (%) |
| S | 303 | |
| C | 98 | 22.1% |
| Q | 43 | 9.7% |
Most occurring scripts
| Value | Count | Frequency (%) |
| Latin | 446 |
| Value | Count | Frequency (%) |
| Latin | 444 |
Most frequent character per script
Latin
| Value | Count | Frequency (%) |
| S | 331 | |
| C | 75 | 16.8% |
| Q | 40 | 9.0% |
| Value | Count | Frequency (%) |
| S | 303 | |
| C | 98 | 22.1% |
| Q | 43 | 9.7% |
Most occurring blocks
| Value | Count | Frequency (%) |
| ASCII | 446 |
| Value | Count | Frequency (%) |
| ASCII | 444 |
Most frequent character per block
ASCII
| Value | Count | Frequency (%) |
| S | 331 | |
| C | 75 | 16.8% |
| Q | 40 | 9.0% |
| Value | Count | Frequency (%) |
| S | 303 | |
| C | 98 | 22.1% |
| Q | 43 | 9.7% |
Dataset A
Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
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Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
Dataset A
Dataset B
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Dataset B
Dataset A
Dataset B
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Dataset B
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Dataset B
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Dataset B
Dataset A
| PassengerId | Age | SibSp | Parch | Fare | Survived | Pclass | Sex | Embarked | |
|---|---|---|---|---|---|---|---|---|---|
| PassengerId | 1.000 | 0.049 | -0.050 | 0.027 | -0.029 | 0.107 | 0.000 | 0.050 | 0.000 |
| Age | 0.049 | 1.000 | -0.170 | -0.177 | 0.139 | 0.146 | 0.252 | 0.085 | 0.079 |
| SibSp | -0.050 | -0.170 | 1.000 | 0.437 | 0.477 | 0.144 | 0.154 | 0.209 | 0.000 |
| Parch | 0.027 | -0.177 | 0.437 | 1.000 | 0.401 | 0.107 | 0.000 | 0.254 | 0.000 |
| Fare | -0.029 | 0.139 | 0.477 | 0.401 | 1.000 | 0.301 | 0.446 | 0.146 | 0.235 |
| Survived | 0.107 | 0.146 | 0.144 | 0.107 | 0.301 | 1.000 | 0.379 | 0.500 | 0.038 |
| Pclass | 0.000 | 0.252 | 0.154 | 0.000 | 0.446 | 0.379 | 1.000 | 0.147 | 0.261 |
| Sex | 0.050 | 0.085 | 0.209 | 0.254 | 0.146 | 0.500 | 0.147 | 1.000 | 0.058 |
| Embarked | 0.000 | 0.079 | 0.000 | 0.000 | 0.235 | 0.038 | 0.261 | 0.058 | 1.000 |
Dataset B
| PassengerId | Age | SibSp | Parch | Fare | Survived | Pclass | Sex | Embarked | |
|---|---|---|---|---|---|---|---|---|---|
| PassengerId | 1.000 | 0.041 | -0.049 | -0.040 | -0.010 | 0.071 | 0.000 | 0.000 | 0.000 |
| Age | 0.041 | 1.000 | -0.184 | -0.273 | 0.144 | 0.173 | 0.265 | 0.100 | 0.000 |
| SibSp | -0.049 | -0.184 | 1.000 | 0.428 | 0.428 | 0.154 | 0.096 | 0.182 | 0.000 |
| Parch | -0.040 | -0.273 | 0.428 | 1.000 | 0.404 | 0.168 | 0.000 | 0.200 | 0.029 |
| Fare | -0.010 | 0.144 | 0.428 | 0.404 | 1.000 | 0.268 | 0.463 | 0.150 | 0.240 |
| Survived | 0.071 | 0.173 | 0.154 | 0.168 | 0.268 | 1.000 | 0.317 | 0.555 | 0.166 |
| Pclass | 0.000 | 0.265 | 0.096 | 0.000 | 0.463 | 0.317 | 1.000 | 0.126 | 0.301 |
| Sex | 0.000 | 0.100 | 0.182 | 0.200 | 0.150 | 0.555 | 0.126 | 1.000 | 0.099 |
| Embarked | 0.000 | 0.000 | 0.000 | 0.029 | 0.240 | 0.166 | 0.301 | 0.099 | 1.000 |
Dataset A
A simple visualization of nullity by column.
Dataset B
A simple visualization of nullity by column.
Dataset A
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
Dataset B
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
Dataset A
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
Dataset B
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
Dataset A
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 361 | 362 | 0 | 2 | del Carlo, Mr. Sebastiano | male | 29.0 | 1 | 0 | SC/PARIS 2167 | 27.7208 | NaN | C |
| 213 | 214 | 0 | 2 | Givard, Mr. Hans Kristensen | male | 30.0 | 0 | 0 | 250646 | 13.0000 | NaN | S |
| 236 | 237 | 0 | 2 | Hold, Mr. Stephen | male | 44.0 | 1 | 0 | 26707 | 26.0000 | NaN | S |
| 328 | 329 | 1 | 3 | Goldsmith, Mrs. Frank John (Emily Alice Brown) | female | 31.0 | 1 | 1 | 363291 | 20.5250 | NaN | S |
| 686 | 687 | 0 | 3 | Panula, Mr. Jaako Arnold | male | 14.0 | 4 | 1 | 3101295 | 39.6875 | NaN | S |
| 114 | 115 | 0 | 3 | Attalah, Miss. Malake | female | 17.0 | 0 | 0 | 2627 | 14.4583 | NaN | C |
| 762 | 763 | 1 | 3 | Barah, Mr. Hanna Assi | male | 20.0 | 0 | 0 | 2663 | 7.2292 | NaN | C |
| 260 | 261 | 0 | 3 | Smith, Mr. Thomas | male | NaN | 0 | 0 | 384461 | 7.7500 | NaN | Q |
| 808 | 809 | 0 | 2 | Meyer, Mr. August | male | 39.0 | 0 | 0 | 248723 | 13.0000 | NaN | S |
| 570 | 571 | 1 | 2 | Harris, Mr. George | male | 62.0 | 0 | 0 | S.W./PP 752 | 10.5000 | NaN | S |
Dataset B
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 580 | 581 | 1 | 2 | Christy, Miss. Julie Rachel | female | 25.0 | 1 | 1 | 237789 | 30.0000 | NaN | S |
| 345 | 346 | 1 | 2 | Brown, Miss. Amelia "Mildred" | female | 24.0 | 0 | 0 | 248733 | 13.0000 | F33 | S |
| 415 | 416 | 0 | 3 | Meek, Mrs. Thomas (Annie Louise Rowley) | female | NaN | 0 | 0 | 343095 | 8.0500 | NaN | S |
| 659 | 660 | 0 | 1 | Newell, Mr. Arthur Webster | male | 58.0 | 0 | 2 | 35273 | 113.2750 | D48 | C |
| 86 | 87 | 0 | 3 | Ford, Mr. William Neal | male | 16.0 | 1 | 3 | W./C. 6608 | 34.3750 | NaN | S |
| 350 | 351 | 0 | 3 | Odahl, Mr. Nils Martin | male | 23.0 | 0 | 0 | 7267 | 9.2250 | NaN | S |
| 710 | 711 | 1 | 1 | Mayne, Mlle. Berthe Antonine ("Mrs de Villiers") | female | 24.0 | 0 | 0 | PC 17482 | 49.5042 | C90 | C |
| 566 | 567 | 0 | 3 | Stoytcheff, Mr. Ilia | male | 19.0 | 0 | 0 | 349205 | 7.8958 | NaN | S |
| 890 | 891 | 0 | 3 | Dooley, Mr. Patrick | male | 32.0 | 0 | 0 | 370376 | 7.7500 | NaN | Q |
| 863 | 864 | 0 | 3 | Sage, Miss. Dorothy Edith "Dolly" | female | NaN | 8 | 2 | CA. 2343 | 69.5500 | NaN | S |
Dataset A
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 325 | 326 | 1 | 1 | Young, Miss. Marie Grice | female | 36.0 | 0 | 0 | PC 17760 | 135.6333 | C32 | C |
| 202 | 203 | 0 | 3 | Johanson, Mr. Jakob Alfred | male | 34.0 | 0 | 0 | 3101264 | 6.4958 | NaN | S |
| 398 | 399 | 0 | 2 | Pain, Dr. Alfred | male | 23.0 | 0 | 0 | 244278 | 10.5000 | NaN | S |
| 651 | 652 | 1 | 2 | Doling, Miss. Elsie | female | 18.0 | 0 | 1 | 231919 | 23.0000 | NaN | S |
| 44 | 45 | 1 | 3 | Devaney, Miss. Margaret Delia | female | 19.0 | 0 | 0 | 330958 | 7.8792 | NaN | Q |
| 638 | 639 | 0 | 3 | Panula, Mrs. Juha (Maria Emilia Ojala) | female | 41.0 | 0 | 5 | 3101295 | 39.6875 | NaN | S |
| 393 | 394 | 1 | 1 | Newell, Miss. Marjorie | female | 23.0 | 1 | 0 | 35273 | 113.2750 | D36 | C |
| 318 | 319 | 1 | 1 | Wick, Miss. Mary Natalie | female | 31.0 | 0 | 2 | 36928 | 164.8667 | C7 | S |
| 101 | 102 | 0 | 3 | Petroff, Mr. Pastcho ("Pentcho") | male | NaN | 0 | 0 | 349215 | 7.8958 | NaN | S |
| 273 | 274 | 0 | 1 | Natsch, Mr. Charles H | male | 37.0 | 0 | 1 | PC 17596 | 29.7000 | C118 | C |
Dataset B
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 556 | 557 | 1 | 1 | Duff Gordon, Lady. (Lucille Christiana Sutherland) ("Mrs Morgan") | female | 48.0 | 1 | 0 | 11755 | 39.6000 | A16 | C |
| 246 | 247 | 0 | 3 | Lindahl, Miss. Agda Thorilda Viktoria | female | 25.0 | 0 | 0 | 347071 | 7.7750 | NaN | S |
| 864 | 865 | 0 | 2 | Gill, Mr. John William | male | 24.0 | 0 | 0 | 233866 | 13.0000 | NaN | S |
| 739 | 740 | 0 | 3 | Nankoff, Mr. Minko | male | NaN | 0 | 0 | 349218 | 7.8958 | NaN | S |
| 98 | 99 | 1 | 2 | Doling, Mrs. John T (Ada Julia Bone) | female | 34.0 | 0 | 1 | 231919 | 23.0000 | NaN | S |
| 550 | 551 | 1 | 1 | Thayer, Mr. John Borland Jr | male | 17.0 | 0 | 2 | 17421 | 110.8833 | C70 | C |
| 477 | 478 | 0 | 3 | Braund, Mr. Lewis Richard | male | 29.0 | 1 | 0 | 3460 | 7.0458 | NaN | S |
| 427 | 428 | 1 | 2 | Phillips, Miss. Kate Florence ("Mrs Kate Louise Phillips Marshall") | female | 19.0 | 0 | 0 | 250655 | 26.0000 | NaN | S |
| 462 | 463 | 0 | 1 | Gee, Mr. Arthur H | male | 47.0 | 0 | 0 | 111320 | 38.5000 | E63 | S |
| 65 | 66 | 1 | 3 | Moubarek, Master. Gerios | male | NaN | 1 | 1 | 2661 | 15.2458 | NaN | C |
Dataset A
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | # duplicates | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dataset does not contain duplicate rows. | |||||||||||||
Dataset B
| PassengerId | Survived | Pclass | Name | Sex | Age | SibSp | Parch | Ticket | Fare | Cabin | Embarked | # duplicates | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dataset does not contain duplicate rows. | |||||||||||||